---------- Forwarded message --------- From: Aditya Singh 5-Yr IDD Mathematics & Computing IIT (BHU) Varanasi<[hidden email]> Date: Mon, Mar 23, 2020 at 9:03 AM Subject: Re: GSoC Project #8 JDERobotics To: <[hidden email]>
I am Aditya Singh, an Integrated Dual Degree(Masters+Bachelors) student pursuing
Mathematics and Computing(Hons.) from the Indian Institute of
Technology(BHU), Varanasi. I’ve developed a passion
for Reinforcement Learning, and I'm intrigued by its research prospects.
I'm decidedly interested in pursuing independent research(PhD). I have
also written a blog(link) on my research interest.
personally interested in Project #8: Reinforcement Learning for Autonomous Driving with Gazebo and OpenAI gym. I'm very much familiar with OpenAI gym and Gazebo, I have also used CARLA Simulator. The projects aim to do some comparisons among the already implemented algorithms. I have created an execution plan please look into it and enrich it with your ideas. I have written a short note which explains why I specifically want to work on Project 8.
Current and previous experience:
Currently, I'm trying to extend Q learning with UCB-Hoeffding bonus to the continuous state space domain. This project part of my stream project, which is under the supervision of Dr. Kailasam Lakshmanan.
2. I have implemented multiple Deep Reinforcement Learning algorithms(including C51, QR-DQN), here are some of them.
3. This summer, I worked with Prof. Rishi Kamaleswaran, The University of Tennessee,
on Fever and Sepsis onset prediction, using CNNs and data science techniques. The abstract and poster for Sepsis Onset prediction are published in HIPOCT’ 19 conferences. The fever onset prediction project was under the umbrella of Google Summer of Code' 19(Completion Letter by Tony Urso, GSoC Program Manager), you can look in the feedback provided by my mentor for more detail.
You can check my CV
for your reference. Feel free to contact the referred professor in the
CV. I am genuinely interested in working with you and come up with quality work in our aligned areas of interest.
Thank you so much for taking the time to read my note. I appreciate your feedback and feel excited to hear back from you soon!